Gaining awareness of the user's affective states enables smartphones to support enriched interactions that are sensitive to the user's context. To accomplish this on smartphones, we propose a system that analyzes the user's text typing behavior using a semi-supervised deep learning pipeline for predicting affective states measured by valence, arousal, and dominance. Using a data collection study with 70 participants on text conversations designed to trigger different affective responses, we developed a variational auto-encoder to learn efficient feature embeddings of two-dimensional heat maps generated from touch data while participants engaged in these conversations. Using the learned embedding in a cross-validated analysis, our system predicted three levels (low, medium, high) of valence (AUC up to 0.84), arousal (AUC up to 0.82), and dominance (AUC up to 0.82). These results demonstrate the feasibility of our approach to accurately predict affective states based only on touch data.
Mobile devices have become the primary mode for Internet access in developing countries. Yet typical data plans and SMS costs can be overwhelming for low income users in these countries. In this paper, we explore the design and usability of a free but extremely low bit rate communication channel to address this challenge. We propose, a data communication channel that uses to transmit messages between phones, thereby sacrificing performance in exchange for low cost. While the data rate of is extremely low (<1 bps), our prototype implementation and small scale user studies explore the feasibility of this idea for different types of messaging scenarios. Our results show that could be a viable option for messaging scenarios that require short, pre-determined responses (e.g., survey questions) while for traditional SMS-style messaging, a suitable user interface and other customizations are likely required to make it a viable option for users.
In this paper, we demonstrate the existence of a bidirectional causal relationship between smartphone application use and user emotions. In a two-week long in-the-wild study with 30 participants we captured 502,851 instances of smartphone application use in tandem with corresponding emotional data from facial expressions. Our analysis shows that while in most cases application use drives user emotions, multiple application categories exist for which the causal effect is in the opposite direction. Our findings shed light on the relationship between smartphone use and emotional states. We furthermore discuss the opportunities for research and practice that arise from our findings and their potential to support emotional well-being.
Translation apps and devices are often presented in the context of providing assistance while traveling abroad. However, the spectrum of needs for cross-language communication is much wider. To investigate these needs, we conducted three studies with populations spanning socioeconomic status and geographic regions: (1) United States-based travelers, (2) migrant workers in India, and (3) immigrant populations in the United States. We compare frequent travelers' perception and actual translation needs with those of the two migrant communities. The latter two, with low language proficiency, have the greatest translation needs to navigate their daily lives. However, current mobile translation apps do not meet these needs. Our findings provide new insights on the usage practices and limitations of mobile translation tools. Finally, we propose design implications to help apps better serve these unmet needs.
Excessive smartphone use has negative effects on our social relations as well as on our mental and psychological health. Most of the previous work to avoid these negative effects is based on a top-down approach such as restricting or limiting users' use of smartphones. Diverging from previous work, we followed a bottom-up approach to understand the practice of smartphone use in public settings from the users' perspective. We conducted observations in four coffeehouses, six focus group sessions with 46 participants and three design workshops with 15 designers. We identified five themes that help better understand smartphone use behavior in public settings and four alternative design approaches to mediate this behavior, namely enlighteners, preventers, supporters, and compliers. We discuss the implications of these themes and approaches for designing future interactive technologies aimed at mediating excessive smartphone use behavior.